Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects high-volume, automated file download or access activity originating from SharePoint Online, OneDrive, or Exchange Online within a 2-hour window. The rule identifies suspicious patterns involving a large number of distinct file events, potentially indicating automated scripts or tools (like python-httpx) performing mass data collection or exfiltration.
Detects anomalous, high-volume file access or download activity in Microsoft SharePoint Online or OneDrive for Business originating from a 'python-httpx' user agent. This pattern often indicates automated data collection or exfiltration attempts using programmatic tools.
Detects anomalous, low-volume data access behavior within cloud applications (such as file downloads, previews, or mail access) that is sustained over an extended period. This pattern often indicates slow, deliberate data exfiltration designed to evade volume-based detection thresholds.
Detects a single user account downloading or accessing a high volume of files (more than 50) within a 15-minute window from SharePoint or OneDrive. This behavior often indicates automated data collection, potential mass exfiltration, or a compromised user account account accessing sensitive files in bulk.
This rule monitors Office 365 activity for anomalous search behavior, specifically targeting high volumes of distinct search queries involving site collections, web structures, or index ID patterns. Such patterns are indicative of automated data discovery or enumeration activities performed against SharePoint or OneDrive environments.
Detects automated directory fuzzing attempts against Azure Storage blobs targeting sensitive files like .env, .pem, or configuration files. The rule identifies suspicious activity by aggregating requests from Anonymous or SAS-authenticated sources that exhibit high request volumes and access to multiple distinct sensitive paths, while excluding known legitimate bulk-transfer and synchronization tools.
Detects high-frequency access requests to SharePoint or OneDrive services using the 'python-httpx' library. This behavior is indicative of automated scraping or mass data retrieval often associated with malicious actors or unauthorized automated tools.
Detects users accessing files across SharePoint, OneDrive, or Exchange over a sustained period of at least 6 hours, while maintaining a low-to-moderate frequency (1-999 events per hour). This behavioral pattern may indicate slow, automated data exfiltration or unauthorized reconnaissance of sensitive files while attempting to stay under traditional volume-based alerting thresholds.
Detects anomalous, high-frequency file access (100+ files within a 2-hour window) in Microsoft 365 (SharePoint or OneDrive) by users employing a Python-based HTTP client (python-httpx). This behavior is often indicative of automated data scraping, exfiltration, or bulk download activities performed by unauthorized scripts or compromised service accounts.
Detects instances where identified AI agents, bots, or automated assistants perform bulk access operations on mailboxes (e.g., MailItemsAccessed, Send, deletions) or data stores (e.g., FileDownloaded, FileAccessed, SearchQueryPerformed) in Microsoft 365 environments. This monitors for potentially compromised or malicious AI service accounts abusing legitimate access to harvest sensitive data.
This rule monitors Office 365 file download activity, identifying users whose download volume significantly deviates from their historical baseline. It specifically looks for an unusually high number of unique files downloaded in a one-hour window, while excluding known service accounts and synchronization agents like OneDrive sync client.
Detects anomalous, large-scale cloning or mirroring of code repositories combined with targeted access to infrastructure-as-code configuration files (e.g., .tfvars, .tfstate) or automated exfiltration of CI/CD build artifacts. This behavior is indicative of an adversary attempting to exfiltrate proprietary source code or sensitive secrets stored within repositories.
Detects anomalous, high-frequency mailbox search and access activity targeting financial-related keywords (e.g., invoices, wire transfers, bank details). This behavior pattern is frequently observed during business email compromise (BEC) attacks, where adversaries utilize OAuth tokens to triage mailboxes for sensitive payment information.
This rule monitors Microsoft Graph API audit logs for suspicious patterns indicative of automated discovery or enumeration of SharePoint and OneDrive environments. It detects high-frequency access to sensitive API endpoints (such as /sites, /drives, or /children) and the use of pagination parameters (skiptoken, top) within short time intervals, which are common techniques used to crawl and inventory organizational data at scale.
This rule monitors Microsoft Graph API audit logs for suspicious patterns indicative of automated discovery or enumeration of SharePoint and OneDrive environments. It detects high-frequency access to sensitive API endpoints (such as /sites, /drives, or /children) and the use of pagination parameters (skiptoken, top) within short time intervals, which are common techniques used to crawl and inventory organizational data at scale.
This rule detects anomalous activity where users access Microsoft 365 services (SharePoint, OneDrive, Exchange) through identified anonymous proxy connections. It identifies potentially malicious exfiltration or bulk activity by flagging users who perform a high number of operations (1,000+ events) or download a significant volume of data (5GB+) within a 2-hour window.
This rule detects potentially malicious or automated data access patterns within Microsoft 365 or similar cloud environments. It identifies user accounts or applications that exhibit a high volume of file/email access operations across a diverse set of paths, which is often indicative of automated data exfiltration, scraping, or suspicious collection by a compromised identity.
Detects automated file access and download operations in SharePoint or OneDrive performed by the 'python-httpx' library. This behavior may indicate an attacker using scripts or automated tools to perform unauthorized data collection or exfiltration, often observed in automated cloud compromise scenarios.
Detects high-volume image pull activity against an Azure Container Registry from a single identity, which may indicate reconnaissance or mass harvesting of container images to extract embedded credentials, secrets, or source code.
Detects anomalous, high-volume activity directed at SharePoint and OneDrive Graph API endpoints (e.g., /sites, /drives, /search, /children). The activity pattern, characterized by multiple distinct path requests and the usage of pagination tokens within a short timeframe, strongly indicates an adversary attempting to map the file structure and contents of a repository prior to data collection or exfiltration.
Detects anomalous, high-volume file access (downloading, accessing, or previewing) in cloud applications that originates from an IP address identified as an anonymous proxy. This behavior is indicative of potential data exfiltration or unauthorized mass data collection.
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